Project ,

Breast Cancer Detection

Deep learning is a type of machine learning based on Artificial Neural Networks in which multiple layers of processing are used to extract progressively higher level features from the data
Course
Curriculum

What will you Learn in the Project?

  1. Loading and exploring the data -Import the stock dataset, and find the shape of the data, explore some values of the data.
  2. Split your dataset into train and test and scale or normalize the data
  3. Normalize your data to make the dataset fit for your model.
  4. Fit the model – Fit your training model by initializing deep learning model parameters and layers.
  5. Validate your model with validation metrics and plot – Validate your model with training and testing dataset and plot the visualization of the predicted and actual data.

All these tasks will cover:

  1. Simple Linear Regression
  2. Understanding Optimizers Execution
  3. Understanding Optimizers
  4. OR Gates Using Keras
  5. CNN Intuition
  6. RNN Intuition
  7. RNN

Requirement

This course does NOT cover the theory part so it assumes that you know the theory of Deep Learning.

Description

This course covers followings:

Demos:

  1. Simple Linear Regression
  2. Understanding Optimizers Execution
  3. Understanding Optimizers
  4. OR Gates Using Keras
  5. CNN Intuition
  6. RNN Intuition
  7. RNN

Projects:

  1. Breast Cancer Detection
You as a Deep learning engineer have to create a solution using deep learning framework by studying the cancer pattern in its image and try to predict whether the pattern in cells formation is a sign of cancer development .
 

2. Stock Market Prediction

Your task is to create a rigorous model that can predict upcoming stock values by learning its history.
 

Who this course is for?

1. College Freshers
2. Anyone who wants to see what are the use cases where Deep Learning applies and how to implement various concepts
3. Any one who wants to start their journey in Artificial Intelligence

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Skills you will develop

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